The present invention pertains to an aircraft-mounted air turbulence warning system in which a measuring device mounted on the aircraft is used to collect air turbulence data, and also random atmosphere simulation is used to supplement the amount of data, thereby predicting air turbulence and emitting a warning based on the collected data.
The following applications have already been submitted in relation to an aircraft-mounted air turbulence warning system.
JP-A-5-508930 discloses a radar device in which a determination as to whether to perform a warning or not is made based on whether or not a wind shear velocity detected by radar is within a specified range.
Further, JP-A-6-500860 discloses a radar system in which air turbulence is determined to exist in the case when deviations in wind velocity detected by aircraft-mounted radar are greater than those in a case of non-turbulence or minor air turbulence with no danger.
Additionally, JP-A-6-500861 discloses a radar system in which a microburst is determined based on a wind velocity measured by an upper radar mounted on the aircraft and a wind shear is determined based on a wind velocity measured by a lower radar, in a case where the velocity exceeds a threshold.
FIG. 10 depicts a conventional aircraft-mounted air turbulence warning system. In FIG. 10, radar is used by the measuring unit 201 to measure airflow around the aircraft. The radar obtains a relative measurement value of the airflow in relation to the aircraft. For example, with reference to FIG. 3, a difference is obtained between an aircraft velocity vector 501 and an aircraft forward directional component 503 of an airflow velocity vector 502. This differential is referred to hereinafter as a measured airflow velocity. Measurement of the measured airflow velocity is made at a plurality of points, and the velocity of the airflow toward each of the points is calculated from the aircraft velocity vector and the measured airflow velocity, so that, assuming that the wind velocity and wind direction are consistent across the various points, the airflow velocity vector can be calculated.
At a determination unit 203 a determination is made as to whether the aircraft is approaching dangerous air turbulence for which a warning should be made. In JP-A-5-508930 this determination is made, for example, based on shear wind velocity, and in JP-A-6-500860 the determination is made on wind velocity deviations, and in JP-A-6-500861 it is made on the wind velocity of the microburst core measured by the upper radar, and the wind velocity of the wind shear measured by the lower radar. The airflow velocity vector is derived from the measured airflow velocity and the aircraft velocity vector, and then reference is made to threshold information 202 to determine whether or not the aircraft is approaching dangerous air turbulence.
Threshold information 202 accumulates a range of values pertinent to the criteria used by the determination unit 203. When the determination unit 203 has determined that the aircraft is approaching a turbulent airflow, a display unit 204 informs the user of that fact.
In an aircraft-mounted air turbulence warning system which uses a format mentioned above as the above prior art, an airflow model is prepared in advance, and the results obtained from measuring the surround airflow are then fitted into the model so that the determination as to whether the aircraft is approaching turbulent flow or not can be performed. For example, in Japanese Patent Translation Publication No. Hei 6-500861 mentioned above, using a model of a whirl and based on an assumption that the aircraft is in flight near a ground surface, which is to say a premise that the aircraft it is passing below a whirl created by airflow, and that a microburst core exists above it and a shear exists below, the measurement results are fitted into these, and when this fits a judgment is determined that the aircraft is approaching a turbulent flow.
Accordingly, in the case when the airflow model is not a precise model, for example, it is not known in advance in the case where the aircraft is flying at high altitudes, which part of the whirl of the air flow the aircraft will encounter, there was a problem that it was impossible to issue the warning.
The present invention was devised in order to solve such a problem; therefore, an object thereof is to obtain an aircraft-mounted air turbulence warning system in which an accumulation of actual data is used as a basis for performing in parallel fashion the building of models by classifying data, the selecting of a model by determining a class to which data belongs and the predicting of air turbulence, producing the result that it is possible to predict the turbulent flow even in the case when the airflow model is not clearly specified in advance.
In an aircraft-mounted air turbulence warning system according to the present invention, there is provided a system in which a measuring device mounted on an aircraft is used to collect air current data for predicting air turbulence and issuing a warning based on this data, the system being provided with:
a parent unit having:
a precedent base for accumulating data notified from a plurality of child units;
an element data determination unit for processing the data in the precedent base, turning it into element data based on a predetermined designation of a range that is subject to this processing, and storing the element data is a classification precedent base;
an element data classification unit for creating an aggregation of element data based on results, which are written in the element data in the classification precedent base, of a determination as to whether the aircraft is to encounter air turbulence, classifying each element data aggregation to create a classification chart and recording this in the classification precedent base;
an element data change classification unit for determining which classification the element data in the classification precedent base belongs to and describing this as a change chart in the classification precedent base, and based on this change chart, summing changes of a classification identifier of each aircraft classification identifier, and calculating transition probabilities among the classifications and describing these as a status transition chart in the classification precedent base;
a classification precedent base for storing the element data, the classification chart, the change chart and the status transition chart; and
a display unit for displaying the change chart and the status transition chart;
and a child unit having:
a measurement unit for collecting the air current data and notifying the data to the precedent base;
a child unit element data determination unit for processing data collected by the measurement unit based on the subject range that was designated as being the subject of the processing and turning it into the element data, and outputting this to a child unit element data class determination unit;
the child unit element data classification determination unit for referencing a mixture distribution chart in the child unit classification precedent base, determining which element distribution in the mixture distribution chart each of the element data processed by the child unit element data determination unit should belong to and informing a child unit display unit of an element distribution identifier which it has determined; and also, referencing the status transition chart, obtaining transition probabilities from the element distribution to all of the element distributions, informing the child unit display unit of these transition probabilities, calculating a probability of encountering air turbulence based on the transition probabilities and whether or not the mixture distribution chart indicates an air turbulence encounter and informing this probability of encountering air turbulence to the child unit display unit;
the child unit classification precedent base for making a request to the classification precedent base and obtaining the classification chart and the status transition chart, and providing these according to a request from the child unit element data classification determination unit; and
the child unit display unit for displaying the class element distribution, the transition probabilities and the probability of encountering air turbulence obtained from the child unit element data classification determination unit, and issuing a warning in the case when the probability of encountering air turbulence satisfies predetermined conditions.
Further, the system is further provided with a random atmospheric modeling unit for using regional data from the vicinity surrounding the parent unit to perform a simulation of airflow, randomly generating a velocity vector and a position for a mock aircraft in this simulation and making this mock aircraft perform a mock flight, generating mock measurement results which should be measured by the measurement unit of the child unit in the case when the child unit were mounted on the mock aircraft and notifying these results to the element data determination unit, and
the element data determination unit processes the data from the precedent base and the random atmospheric modeling unit in accordance with the predetermined range being designated as the subject of this processing and turns the data into the element data, and records this in the classification precedent base.
Further, classification is performed by, assuming a mixture distribution made up of a plurality of distributions, estimating the mixing proportions and the mixture distribution parameters of the element distributions;
the classification precedent base accumulates correspondences between the mixture distribution parameters and the element distribution identifiers, and correspondences between the element distribution identifiers and the element data;
the element data classification unit inputs the number of distributions assumed to be mixed, obtains mixture distribution parameters by preparing the element data as the mixture distribution based on the mixture number and records in the classification precedent base correspondences between the mixture distribution identifiers and the mixture distribution parameters; and
the child unit element data classification determination unit determines which element distribution the element data belongs to, and records in the classification precedent base correspondences between the element data and the element distribution identifiers corresponding to the element data.
Further, the element distribution is a multi-dimensional normal distribution having no covariance component, and mixture distribution parameters are sought for a mixture distribution made up of a predetermined number of the element distributions to be added that are added with weights, and correspondences between the mixture distribution identifiers and the mixture distribution parameters are recorded in the classification precedent base;
the element data change classification unit makes each element data belong to the element distribution in which the product of the probability density of the element data of that element distribution and the mixing proportion for that element distribution is the greatest of all the element distributions, and
the element data classification unit performs the following steps of:
a subject range investigation step in which an average, a variance; a number of types of values and a total number of values which are not null values are investigated with respect to each attribute;
an initial distribution generation step in which the initial distribution for an element distribution, which has the initial values such that the average values of the attributes are to be average values which are mutually different from each other with respect to the items being measured for which there are a predetermined number or more of types of values, and for measured items having less than the predetermined number of types of values, the average values are chosen from among the types of values, and for the variance, an appropriate number such as a number other than 0 is obtained, is generated for a number equal to the number of classifications;
a repeating improvement step having an expectation value calculation sub-step, in which provisional averages, variances and mixing proportion for each of the element distributions are used as a basis to calculate probability density for each of the data elements; an element distribution updating sub-step S232, in which for each element data a probability density ratio is calculated for each provisional element distribution and is used as a proportion of contribution therefrom, for each element distribution the contribution is multiplied by the values of each element data to obtain a value, the number of pieces of element data is obtained as a sum total of the respective proportions of contribution, and this value and this sum total are used as a basis for a new average and a variance for the provisional element distribution; and a completion determination sub-step, in which changes in, the parameter combinations of the provisional distribution are monitored, and the repeating improvement ends when the parameter combination does not change during the course of the number of repetitions, or when the same parameter combination repeatedly appears a predetermined number of times, or when the number of repetitions has been executed a predetermined number of times; and
a completion step, in which the parameter combination which has been obtained is recorded into the classification precedent base together with an element distribution identifier.
Additionally, the repeating improvement step comprises the following steps of:
an expectation value calculation sub-step, in which provisional averages, variances and mixing proportion for each of the element distributions are used as a basis to calculate probability density for each of the element data, an annealing parameter greater than 0 and equal to or less than 1 is used to record the probability density raised to the power of the annealing parameter;
an element distribution updating sub-step, in which for each element data the ratio among the probability densities for each provisional element distribution, which have been raised to the power of the annealing parameter and recorded in the initial value calculation sub-step, is calculated and this is used as a proportion of contribution therefrom, for each element distribution the contribution is multiplied by the values of each element data to obtain a value, the number of pieces of element data is obtained as a sum total of the respective proportions of contribution, and this value and this sum total are used as a basis for a new average and variance for the provisional element distribution;
a completion determination sub-step, in which changes in the parameter combinations of the provisional distribution are monitored, and the repetition of the annealing parameter ends when the parameter combination does not change during the course of the number of repetitions, or when the same parameter combination repeatedly appears a predetermined number of times, or when the number of repetitions has been executed a predetermined number of times; and
an annealing sub-step, in which the outer side of the repetition is ended in the case when the value of the annealing parameter is increased in accordance with a predetermined plan, the procedure subsequent to the anticipated value calculation sub-step is repeated and the annealing parameter has become equal to or greater than 1.